Educational attainment (EduA) is correlated with life outcomes, and EduA itself is influenced by both cognitive and non-cognitive factors. A recent study performed a ‘genome-wide association study (GWAS) by subtraction,’ subtracting genetic effects for cognitive performance from an educational attainment GWAS to create orthogonal ‘cognitive’ and ‘non-cognitive’ factors. These cognitive and non-cognitive factors showed associations with behavioral health outcomes in adults; however, whether these correlations are present during childhood is unclear.

Using data from up to 5517 youth (ages 9–11) of European ancestry from the ongoing Adolescent Brain Cognitive DevelopmentSM Study, we examined associations between polygenic scores (PGS) for cognitive and non-cognitive factors and cognition, risk tolerance, decision-making & personality, substance initiation, psychopathology, and brain structure (e.g. volume, fractional anisotropy [FA]). Within-sibling analyses estimated whether observed genetic associations may be consistent with direct genetic effects.

Both PGSs were associated with greater cognition and lower impulsivity, drive, and severity of psychotic-like experiences. The cognitive PGS was also associated with greater risk tolerance, increased odds of choosing delayed reward, and decreased likelihood of ADHD and bipolar disorder; the non-cognitive PGS was associated with lack of perseverance and reward responsiveness. Cognitive PGS were more strongly associated with larger regional cortical volumes; non-cognitive PGS were more strongly associated with higher FA. All associations were characterized by small effects.

While the small sizes of these associations suggest that they are not effective for prediction within individuals, cognitive and non-cognitive PGS show unique associations with phenotypes in childhood at the population level.

Although the link between alcohol involvement and behavioral phenotypes (e.g. impulsivity, negative affect, executive function [EF]) is well-established, the directionality of these associations, specificity to stages of alcohol involvement, and extent of shared genetic liability remain unclear. We estimate longitudinal associations between transitions among alcohol milestones, behavioral phenotypes, and indices of genetic risk.

Data came from the Collaborative Study on the Genetics of Alcoholism (n = 3681; ages 11–36). Alcohol transitions (first: drink, intoxication, alcohol use disorder [AUD] symptom, AUD diagnosis), internalizing, and externalizing phenotypes came from the Semi-Structured Assessment for the Genetics of Alcoholism. EF was measured with the Tower of London and Visual Span Tasks. Polygenic scores (PGS) were computed for alcohol-related and behavioral phenotypes. Cox models estimated associations among PGS, behavior, and alcohol milestones.

Externalizing phenotypes (e.g. conduct disorder symptoms) were associated with future initiation and drinking problems (hazard ratio (HR)⩾1.16). Internalizing (e.g. social anxiety) was associated with hazards for progression from first drink to severe AUD (HR⩾1.55). Initiation and AUD were associated with increased hazards for later depressive symptoms and suicidal ideation (HR⩾1.38), and initiation was associated with increased hazards for future conduct symptoms (HR = 1.60). EF was not associated with alcohol transitions. Drinks per week PGS was linked with increased hazards for alcohol transitions (HR⩾1.06). Problematic alcohol use PGS increased hazards for suicidal ideation (HR = 1.20).

Behavioral markers of addiction vulnerability precede and follow alcohol transitions, highlighting dynamic, bidirectional relationships between behavior and emerging addiction.

As the US population ages, the prevalence of Alzheimer’s disease and related dementias (AD/RD) is on the rise. This is especially true in rural America, where mortality rates due to AD/RD are rising faster than in metropolitan areas. To date, however, people living in rural communities are severely underrepresented in aging research. The Nevada Exploratory Alzheimer’s Disease Research Center (NVeADRC) seeks to address this gap. Here, we present preliminary cognitive data from our rural-dwelling cohort, as well as relevant demographic and clinical characteristics.

Individuals with normal cognition (NC), mild cognitive impairment (MCI), and dementia due to Alzheimer’s disease (AD) living in rural communities, defined as a rural-urban commuting area (RUCA) code of 4 or higher, were enrolled through either clinic or community outreach. Eligibility for the observational cohort required: age >55 years, primarily English-speaking, primary residence in a rural community, and availability of a study partner. Measures included the Uniform Data Set (v3), blood-based biomarkers, structural brain MRI, and portions of the PhenX Social Determinants of Health toolkit. Participants are seen at baseline and followed annually, with interim remote visits every 6 months. A multidisciplinary consensus diagnosis is rendered after each visit. Where feasible, a harmonized urban cohort followed by the Nevada Center for Neurodegeneration and Translational Neuroscience (CNTN) was used for comparison.

Fifty-six rural-dwelling (age=70.4±7.1 years; edu=15.2±2.6 years; 61% female) and 148 urban-dwelling (age=72.9±6.8 years; edu=15.8±2.7 years; 46% female) older adults were included; age significantly differed between cohorts but education did not. The rural cohort was 46% NC (MoCA=26.8±2.3; CDRsob=0.3±0.6), 32% MCI (MoCA=22.8±3.1; CDRsob=1.2±1.0), and 22% AD (MoCA=16.9±5.5; CDRsob=5.2±3.0). The urban cohort was 39% NC (MoCA=26.4±2.6; CDRsob=0.3±0.8), 44% MCI (MoCA=22.3±3.1; CDRsob=2.0±1.5) and 17% AD (MoCA=18.6±3.9; CDRsob=4.7±2.3). Rural communities were significantly more disadvantaged, as measured by the Area Deprivation Index (ADI), than urban communities (rural ADI=6.3±2.6; urban ADI=3.4±2.3; p<.001). Fifty-percent of the rural cohort lives in a moderate to severely disadvantaged neighborhood (ADI Decile>7) compared to 12% of the urban cohort, and 11% of individuals in the rural cohort reported living more than 30 miles from the nearest medical facility. Across the combined cohort, education was significantly correlated with ADI deciles (r=-.30, p<.001), with people in the areas of highest disadvantage having the lowest education. Verbal memory was also inversely associated with ADI. There were no differences in clinical diagnosis as a function of ADI rank.

Living in a rural community conveys a multifaceted array of risks and benefits, some of which differ from urban settings. The literature to date suggests that older adults living in rural communities are at significantly increased risk for morbidity and mortality due to AD/RD, though it is unclear why. Preliminary data from the NVeADRC show that increasing levels of neighborhood disadvantage were associated with lower levels of education and worse verbal memory in this convenience sample. The combined effect of low education and increased disadvantage account for some of the urban-rural differences in mortality that have been reported, though additional research on representative samples in this underrepresented population is critical.

To estimate the incidence, duration and risk factors for diagnostic delays associated with pertussis.

We used longitudinal retrospective insurance claims from the Marketscan Commercial Claims and Encounters, Medicare Supplemental (2001–2020), and Multi-State Medicaid (2014–2018) databases.

Inpatient, emergency department, and outpatient visits.

The study included patients diagnosed with pertussis (International Classification of Diseases [ICD] codes) and receipt of macrolide antibiotic treatment.

We estimated the number of visits with pertussis-related symptoms before diagnosis beyond that expected in the absence of diagnostic delays. Using a bootstrapping approach, we estimated the number of visits representing a delay, the number of missed diagnostic opportunities per patient, and the duration of delays. Results were stratified by age groups. We also used a logistic regression model to evaluate potential factors associated with delay.

We identified 20,828 patients meeting inclusion criteria. On average, patients had almost 2 missed opportunities prior to diagnosis, and delay duration was 12 days. Across age groups, the percentage of patients experiencing a delay ranged from 29.7% to 37.6%. The duration of delays increased considerably with age from an average of 5.6 days for patients aged <2 years to 13.8 days for patients aged ≥18 years. Factors associated with increased risk of delays included emergency department visits, telehealth visits, and recent prescriptions for antibiotics not effective against pertussis.

Diagnostic delays for pertussis are frequent. More work is needed to decrease diagnostic delays, especially among adults. Earlier case identification may play an important role in the response to outbreaks by facilitating treatment, isolation, and improved contact tracing.

This is a cross-sectional study aiming to understand the early characteristics and background of bone health impairment in clinically well children with Fontan circulation.

We enrolled 10 clinically well children with Fontan palliation (operated >5 years before study entrance, Tanner stage ≤3, age 12.1 ± 1.77 years, 7 males) and 11 healthy controls (age 12.0 ± 1.45 years, 9 males) at two children’s hospitals. All patients underwent peripheral quantitative CT. For the Fontan group, we obtained clinical characteristics, NYHA class, cardiac index by MRI, dual x-ray absorptiometry, and biochemical studies. Linear regression was used to compare radius and tibia peripheral quantitative CT measures between Fontan patients and controls.

All Fontan patients were clinically well (NYHA class 1 or 2, cardiac index 4.85 ± 1.51 L/min/m2) and without significant comorbidities. Adjusted trabecular bone mineral density, cortical thickness, and bone strength index at the radius were significantly decreased in Fontan patients compared to controls with mean differences −30.13 mg/cm3 (p = 0.041), −0.31 mm (p = 0.043), and −6.65 mg2/mm4 (p = 0.036), respectively. No differences were found for tibial measures. In Fontan patients, the mean height-adjusted lumbar bone mineral density and total body less head z scores were −0.46 ± 1.1 and −0.63 ± 1.1, respectively, which are below the average, but within normal range for age and sex.

In a clinically well Fontan cohort, we found significant bone deficits by peripheral quantitative CT in the radius but not the tibia, suggesting non-weight-bearing bones may be more vulnerable to the unique haemodynamics of the Fontan circulation.

The U.S. Food and Drug Administration (FDA) traditionally has kept confidential significant amounts of information relevant to the approval or non-approval of specific drugs, devices, and biologics and about the regulatory status of such medical products in FDA’s pipeline.

To develop practical recommendations for FDA to improve its transparency to the public that FDA could implement by rulemaking or other regulatory processes without further congressional authorization. These recommendations would build on the work of FDA’s Transparency Task Force in 2010.

In 2016-2017, we convened a team of academic faculty from Harvard Medical School, Brigham and Women’s Hospital, Yale Medical School, Yale Law School, and Johns Hopkins Bloomberg School of Public Health to develop recommendations through an iterative process of reviewing FDA’s practices, considering the legal and policy constraints on FDA in expanding transparency, and obtaining insights from independent observers of FDA.

The team developed 18 specific recommendations for improving FDA’s transparency to the public. FDA could adopt all these recommendations without further congressional action.

The development of the Blueprint for Transparency at the U.S. Food and Drug Administration was funded by the Laura and John Arnold Foundation.

Inpatient length of stay (LOS) has been used as a measure of hospital quality and efficiency. Patients with Clostridium difficile infections (CDI) have longer LOS.

To describe the relationship between hospital CDI incidence and the LOS of patients without CDI.

Retrospective cohort analysis.

We predicted average LOS for patients without CDI at both the hospital and patient level using hospital CDI incidence. We also controlled for hospital characteristics (eg, bed size) and patient characteristics (eg, comorbidities, age).

Healthcare Cost and Utilization Project Nationwide Inpatient Sample, 2009–2011.

The Nationwide Inpatient Sample includes patients from a 20% sample of all nonfederal US hospitals.

Inpatient LOS was significantly longer (P<.001) at hospitals with greater CDI incidence at both the hospital and individual level. At a hospital level, a percentage point increase in the CDI incidence rate was associated with more than an additional day’s stay (between 1.19 and 1.61 days). At the individual level, controlling for all observable variables, a percentage point increase in the CDI incidence rate at their hospital was also associated with longer LOS (between 0.6 and 1.05 additional days). Hospital CDI incidence had a larger impact on LOS than many other commonly used predictors of LOS.

CDI rates are a predictor of LOS in patients without CDI at an individual and institutional level. CDI rates are easy to measure and report and thus may provide an important marker for hospital efficiency and/or quality.

Infect. Control Hosp. Epidemiol. 2016;37(4):404–410